论文标题
传感器辅助块匹配算法，用于通过深度图的翻译运动估算
Sensor-aided block matching algorithm for translational motion estimation through a depth map
论文作者
论文摘要
许多嵌入在智能手机，无人机或内部汽车上的摄像头可以直接访问陀螺仪和加速度计的外部运动感应。在这些功率有限的设备上，视频压缩必须具有低复杂性。因此，我们提出了一种“传感器辅助块匹配算法”，该算法利用了与摄像机同步的运动传感器的存在，以减少框架间视频编解码器中运动估计过程的复杂性。我们的解决方案将先前对旋转运动估计的工作扩展到通过深度图对翻译运动的原始估计。与优化的块匹配运动补偿框架间视频编解码器相比，所提出的算法的复杂性降低系数约为2.5，同时保持了高图像质量并作为场景的深度图提供。
A large number of cameras embedded on smart-phones, drones or inside cars have a direct access to external motion sensing from gyroscopes and accelerometers. On these power-limited devices, video compression must be of low-complexity. For this reason, we propose a "Sensor-Aided Block Matching Algorithm" which exploits the presence of a motion sensor synchronized with a camera to reduce the complexity of the motion estimation process in an inter-frame video codec. Our solution extends the work previously done on rotational motion estimation to an original estimation of the translational motion through a depth map. The proposed algorithm provides a complexity reduction factor of approximately 2.5 compared to optimized block-matching motion compensated inter-frame video codecs while maintaining high image quality and providing as by-product a depth map of the scene.
